大学化学

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分析化学课程AI协作教学的改革探索——课程论文学习任务的重构

杨千帆, 张金懿, 郑成斌, 李峰, 蒲雪梅   

  1. 四川大学化学学院, 四川 成都 610064
  • 收稿日期:2025-11-21 录用日期:2026-01-07
  • 通讯作者: 蒲雪梅, 李峰 E-mail:xmpuscu@scu.edu.cn;windtalker_1205@scu.edu.cn Xuemei Pu, Feng Li
  • 基金资助:
    四川省高等教育人才培养质量和教学改革项目(JG2024-0092)

Reform exploration of AI-assisted teaching in analytical chemistry courses: Restructuring the learning task of course paper

Qianfan Yang, Jinyi Zhang, Chengbin Zheng, Feng Li, Xuemei Pu   

  1. College of Chemistry, Sichuan University, Chengdu 610064, Sichuan Province, China
  • Received:2025-11-21 Accepted:2026-01-07
  • Contact: Xuemei Pu, Feng Li E-mail:xmpuscu@scu.edu.cn;windtalker_1205@scu.edu.cn

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摘要： 生成式人工智能的崛起对高等教育传统学习和考核模式构成严峻挑战。为应对此挑战，本研究以分析化学课程中的“课程论文”为改革抓手，旨在探索一条将AI深度融入教学、并以此培养学生高阶思维与人机协作能力的有效路径。研究提出了从“结果呈现”转向“思维呈现”的核心理念，构建了“阅读–提问–对话–判断–反思”的AI协作学习链条，并从提示词工程训练、重构“问题列表-AI对话-学生反思”的三段式论文结构、以及建立以思维质量为核心的评价机制三个维度进行了系统性的教学实践，成功将课程论文从知识复述转变为可视化的思维训练过程。本研究证实：通过精心的教学设计，AI能够成为激发而非替代学生思考的“思维伙伴”，该模式为AI时代理工科专业课程的教学改革提供了具有借鉴意义的实践案例。

关键词: 分析化学, 人工智能, 课程论文, 重构

Abstract: The emergence of generative artificial intelligence presents substantial challenges to conventional learning and assessment paradigms in higher education. Addressing this challenge, our study focuses on reforming the "course paper" component in analytical chemistry courses to investigate an effective approach for deeply integrating AI into instruction while fostering students’ higher-order thinking and human-AI collaboration competencies. We propose a fundamental paradigm shift from “result presentation” to “thinking presentation”, establishing an AI-assisted learning framework comprising “reading-questioning-dialoguing-judging-reflecting”. Through systematic implementation across three key dimensions—prompt engineering training, restructuring the paper format into a tripartite structure (question list, AI dialogue, and student reflection), and developing a thinking-quality-focused evaluation system—we have successfully transformed the course paper from a knowledge-reproduction exercise into a visualized thinking-training process. This study demonstrates that with deliberate instructional design, AI can effectively serve as a “cognitive partner” that stimulates rather than supplants student thinking. The proposed model offers a valuable reference for pedagogical reform in science and engineering disciplines during the AI era.

Key words: Analytical chemistry, Artificial intelligence, Course paper, Restructuring